Image processing1 introduction

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  • Real world is continuous – an image is simply a digital approximation of this.
  • Give the analogy of the character recognition system. Low Level: Cleaning up the image of some text Mid level: Segmenting the text from the background and recognising individual characters High level: Understanding what the text says
  • Image processing1 introduction

    1. 1. Digital Image Processing: Introduction Brian Mac Namee Brian.MacNamee@comp.dit.ie Course Website: http://www.comp.dit.ie/bmacnamee
    2. 2. 2of36 Introduction “One picture is worth more than ten thousand words” Anonymous
    3. 3. 3of36 Miscellanea Lectures: – Thursdays 12:00 – 13:00 – Fridays 15:00 – 16:00 Labs: – Wednesdays 09:00 – 11:00 Web Site: www.comp.dit.ie/bmacnamee/ – Previous year’s slides are available here – Slides etc will also be available on WebCT E-mail: Brian.MacNamee@dit.ie
    4. 4. 4of36 References “Digital Image Processing”, Rafael C. Gonzalez & Richard E. Woods, Addison-Wesley, 2002 – Much of the material that follows is taken from this book “Machine Vision: Automated Visual Inspection and Robot Vision”, David Vernon, Prentice Hall, 1991 – Available online at: homepages.inf.ed.ac.uk/rbf/BOOKS/VERNON/
    5. 5. 5of36 Contents This lecture will cover: – What is a digital image? – What is digital image processing? – History of digital image processing – State of the art examples of digital image processing – Key stages in digital image processing
    6. 6. 6 of 36 What is a Digital Image? A digital image is a representation of a two-Images taken from Gonzalez & Woods, Digital Image Processing (2002) dimensional image as a finite set of digital values, called picture elements or pixels
    7. 7. 7 of 36 What is a Digital Image? (cont…) Pixel values typically represent gray levels,Images taken from Gonzalez & Woods, Digital Image Processing (2002) colours, heights, opacities etc Remember digitization implies that a digital image is an approximation of a real scene 1 pixel
    8. 8. 8of36 What is a Digital Image? (cont…) Common image formats include: – 1 sample per point (B&W or Grayscale) – 3 samples per point (Red, Green, and Blue) – 4 samples per point (Red, Green, Blue, and “Alpha”, a.k.a. Opacity) For most of this course we will focus on grey-scale images
    9. 9. 9of36 What is Digital Image Processing? Digital image processing focuses on two major tasks – Improvement of pictorial information for human interpretation – Processing of image data for storage, transmission and representation for autonomous machine perception Some argument about where image processing ends and fields such as image analysis and computer vision start
    10. 10. 10of36 What is DIP? (cont…) The continuum from image processing to computer vision can be broken up into low-, mid- and high-level processes Low Level Process Mid Level Process High Level Process Input: Image Input: Image Input: Attributes Output: Image Output: Attributes Output: Understanding Examples: Noise Examples: Object Examples: Scene removal, image recognition, understanding, sharpening segmentation autonomous navigation In this course we will stop here
    11. 11. 11 of 36 History of Digital Image Processing Early 1920s: One of the first applications ofImages taken from Gonzalez & Woods, Digital Image Processing (2002) digital imaging was in the news- paper industry – The Bartlane cable picture transmission service Early digital image – Images were transferred by submarine cable between London and New York – Pictures were coded for cable transfer and reconstructed at the receiving end on a telegraph printer
    12. 12. 12 of 36 History of DIP (cont…) Mid to late 1920s: Improvements to theImages taken from Gonzalez & Woods, Digital Image Processing (2002) Bartlane system resulted in higher quality images – New reproduction processes based on photographic techniques – Increased number of tones in Improved digital image Early 15 tone digital reproduced images image
    13. 13. 13 of 36 History of DIP (cont…) 1960s: Improvements in computingImages taken from Gonzalez & Woods, Digital Image Processing (2002) technology and the onset of the space race led to a surge of work in digital image processing – 1964: Computers used to improve the quality of images of the moon taken by the Ranger 7 probe – Such techniques were used A picture of the moon taken in other space missions by the Ranger 7 probe including the Apollo landings minutes before landing
    14. 14. 14 of 36 History of DIP (cont…) 1970s: Digital image processing begins toImages taken from Gonzalez & Woods, Digital Image Processing (2002) be used in medical applications – 1979: Sir Godfrey N. Hounsfield & Prof. Allan M. Cormack share the Nobel Prize in medicine for the invention of tomography, the technology behind Computerised Axial Typical head slice CAT Tomography (CAT) scans image
    15. 15. 15of36 History of DIP (cont…) 1980s - Today: The use of digital image processing techniques has exploded and they are now used for all kinds of tasks in all kinds of areas – Image enhancement/restoration – Artistic effects – Medical visualisation – Industrial inspection – Law enforcement – Human computer interfaces
    16. 16. 16 of 36 Examples: Image Enhancement One of the most common uses of DIPImages taken from Gonzalez & Woods, Digital Image Processing (2002) techniques: improve quality, remove noise etc
    17. 17. 17of36 Examples: The Hubble Telescope Launched in 1990 the Hubble telescope can take images of very distant objects However, an incorrect mirror made many of Hubble’s images useless Image processing techniques were used to fix this
    18. 18. 18of36 Examples: Artistic Effects Artistic effects are used to make images more visually appealing, to add special effects and to make composite images
    19. 19. 19 of 36 Examples: Medicine Take slice from MRI scan of canine heart,Images taken from Gonzalez & Woods, Digital Image Processing (2002) and find boundaries between types of tissue – Image with gray levels representing tissue density – Use a suitable filter to highlight edges Original MRI Image of a Dog Heart Edge Detection Image
    20. 20. 20 of 36 Examples: GIS Geographic Information SystemsImages taken from Gonzalez & Woods, Digital Image Processing (2002) – Digital image processing techniques are used extensively to manipulate satellite imagery – Terrain classification – Meteorology
    21. 21. 21 of 36 Examples: GIS (cont…) Night-Time Lights ofImages taken from Gonzalez & Woods, Digital Image Processing (2002) the World data set – Global inventory of human settlement – Not hard to imagine the kind of analysis that might be done using this data
    22. 22. 22 of 36 Examples: Industrial Inspection Human operators areImages taken from Gonzalez & Woods, Digital Image Processing (2002) expensive, slow and unreliable Make machines do the job instead Industrial vision systems are used in all kinds of industries Can we trust them?
    23. 23. 23of36 Examples: PCB Inspection Printed Circuit Board (PCB) inspection – Machine inspection is used to determine that all components are present and that all solder joints are acceptable – Both conventional imaging and x-ray imaging are used
    24. 24. 24 of 36 Examples: Law Enforcement Image processingImages taken from Gonzalez & Woods, Digital Image Processing (2002) techniques are used extensively by law enforcers – Number plate recognition for speed cameras/automated toll systems – Fingerprint recognition – Enhancement of CCTV images
    25. 25. 25of36 Examples: HCI Try to make human computer interfaces more natural – Face recognition – Gesture recognition Does anyone remember the user interface from “Minority Report”? These tasks can be extremely difficult
    26. 26. 26of36 Key Stages in Digital Image Processing Image Morphological Restoration Processing Image Segmentation Enhancement Image Object Acquisition Recognition Representation Problem Domain & Description Colour Image Image Processing Compression
    27. 27. 27 of Key Stages in Digital Image Processing: 36 Image AquisitionImages taken from Gonzalez & Woods, Digital Image Processing (2002) Image Morphological Restoration Processing Image Segmentation Enhancement Image Object Acquisition Recognition Representation Problem Domain & Description Colour Image Image Processing Compression
    28. 28. 28 of Key Stages in Digital Image Processing: 36 Image EnhancementImages taken from Gonzalez & Woods, Digital Image Processing (2002) Image Morphological Restoration Processing Image Segmentation Enhancement Image Object Acquisition Recognition Representation Problem Domain & Description Colour Image Image Processing Compression
    29. 29. 29 of Key Stages in Digital Image Processing: 36 Image RestorationImages taken from Gonzalez & Woods, Digital Image Processing (2002) Image Morphological Restoration Processing Image Segmentation Enhancement Image Object Acquisition Recognition Representation Problem Domain & Description Colour Image Image Processing Compression
    30. 30. 30 of Key Stages in Digital Image Processing: 36 Morphological ProcessingImages taken from Gonzalez & Woods, Digital Image Processing (2002) Image Morphological Restoration Processing Image Segmentation Enhancement Image Object Acquisition Recognition Representation Problem Domain & Description Colour Image Image Processing Compression
    31. 31. 31 of Key Stages in Digital Image Processing: 36 SegmentationImages taken from Gonzalez & Woods, Digital Image Processing (2002) Image Morphological Restoration Processing Image Segmentation Enhancement Image Object Acquisition Recognition Representation Problem Domain & Description Colour Image Image Processing Compression
    32. 32. 32 of Key Stages in Digital Image Processing: 36 Object RecognitionImages taken from Gonzalez & Woods, Digital Image Processing (2002) Image Morphological Restoration Processing Image Segmentation Enhancement Image Object Acquisition Recognition Representation Problem Domain & Description Colour Image Image Processing Compression
    33. 33. 33 of Key Stages in Digital Image Processing: 36 Representation & DescriptionImages taken from Gonzalez & Woods, Digital Image Processing (2002) Image Morphological Restoration Processing Image Segmentation Enhancement Image Object Acquisition Recognition Representation Problem Domain & Description Colour Image Image Processing Compression
    34. 34. 34of Key Stages in Digital Image Processing:36 Image Compression Image Morphological Restoration Processing Image Segmentation Enhancement Image Object Acquisition Recognition Representation Problem Domain & Description Colour Image Image Processing Compression
    35. 35. 35of Key Stages in Digital Image Processing:36 Colour Image Processing Image Morphological Restoration Processing Image Segmentation Enhancement Image Object Acquisition Recognition Representation Problem Domain & Description Colour Image Image Processing Compression
    36. 36. 36of36 Summary We have looked at: – What is a digital image? – What is digital image processing? – History of digital image processing – State of the art examples of digital image processing – Key stages in digital image processing Next time we will start to see how it all works…

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